IBM yesterday announced the launch of “Project DataWorks”, part of its Watson initiative that aims to exploit artificial intelligence to help businesses and data professionals in the decision-making process.
Technology has made is easier to collect, organize and store data about every single action we take. Businesses these days can generate tons of data points that can capture every single transaction that happens. But the problem is, the data collection part has become so simple that deriving actionable ideas from them has become a harder task than ever before.
As a result, big tech companies are now leveraging the power of artificial intelligence to bridge the gap between data collection and generating “actionable intelligence“ using that data to guide the user to the right decision.
Cloud companies such as Amazon, Microsoft, IBM and Salesforce are leading the charge to make AI a part of our lives. We are already seeing the proliferation of bots that can chat with us: Facebook uses bots on its Messenger app, we have Cortana from Microsoft, Siri from Apple and the list goes on. This is just one component of AI capability exploited by big tech companies to serve end users like you and I, and involves being able to find and present information.
These companies are now taking things a step further and trying to integrate AI in the decision making process as well. Using the data, they apply advanced analytics, machine learning, deep learning, neural networks, natural language processing and several other AI components to help bring us even closer to making decisions. This enabling is what IBM’s latest project is all about. Project DataWorks, according to IBM, is built to create insights for business users through “cognitive-based machine learning”:
“Businesses today understand the competitive advantage of gaining insights from data. However, obtaining those insights can be increasingly complex, and most of this work is done by highly skilled data professionals who work in silos with disconnected tools and data services that may be difficult to manage, integrate, and govern. Also, because data is never static, businesses must continually iterate their data models and products—often manually—to benefit from the most relevant, up-to-date insights.
Now, instead of spending time finding and preparing data for analysis, users can focus their efforts on the core mission – uncovering business-changing insights.
Available on Bluemix, IBM’s Cloud platform, Project DataWorks can help to redefine how data professionals collaborate by tapping into a number of key innovations, such as Apache Spark,IBM Watson Analytics, and the IBM Data Science Experience.” – IBM Press Release
Most data analysis and much of the decision making is done by professionals referred to as data scientists. These are highly trained positions that require a huge amount of skill and ability and, as such, are expensive resources for a company to deploy. In addition, it’s not an easy job, requiring the person to continuously keep building and updating models that can extract data, correlate it and create a snapshot for the decision-maker.
With artificial intelligence, however, the job is made much easier. While it will eliminate much of the manual labor involved, we do not expect tools like DataWorks to replace data scientists in the near future. The decision-making process is far more complex than current AI capabilities can fully handle, and at the core of any decision-making process are human qualities such as creativity, lateral thinking and so on. Machines are getting better at understanding these human nuances that make us…well, human, but they are still a long way from being able to exhibit these characteristics themselves even if they can mimic them in certain situations.
But the fact remains that tools such as this will be immensely helpful in making data scientists more efficient, and helping decision-makers make more informed choices as far as their businesses are concerned. And IBM stands out in this regard because this will be the first time such a system is capable of integrating “all data types” into the process, a major achievement in itself because of the many forms of structured and unstructured data are currently available in, such as videos, images, charts, graphs, tables, text, sound clips and so on.
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